Anemia among pregnant women in Cambodia: A descriptive analysis of temporal and geospatial trends and logistic regression-based examination of factors associated with anemia in pregnant women

Anemia is a major public health problem for thirty-two million pregnant women worldwide. Anemia during pregnancy is a leading cause of child low birth weight, preterm birth, and perinatal/neonatal mortality. Pregnant women are at higher risk of anemia due to micronutrient deficiencies, hemoglobinopathies, infections, socio-demographic and behavioral factors. This study aimed to: 1) assess temporal and geospatial trends of anemia in Cambodia and 2) identify factors associated with anemia among pregnant women aged 15–49 years old in Cambodia. We analyzed data from the Cambodia Demographic and Health Survey (CDHS) for 2005, 2010, and 2014. Data were pooled across the three survey years for all pregnant women aged 15–49 years. Survey weights were applied to account for the complex survey design of the CDHS. Descriptive statistics were estimated for key sociodemographic characteristics of the study population. We used logistic regressions to assess factors associated with anemia among pregnant women aged 15–49 years old. Anemia in pregnant women aged 15–49 in Cambodia decreased from 56% in 2005 to 53% in 2014. With the highest in Preah Vihear and Stung Treng provinces (74.3%), in Kratie province (73%), and in Prey Veng (65.4%) in 2005, 2010, and 2014 respectively. Compared to pregnant women from the wealthiest households, women from poorest households were more likely to have anemia (AOR = 2.8; 95% CI: 1.6–4.9). Pregnant women from coastal regions were almost twice as likely of having anemia (AOR = 1.9; 95% CI: 1.2–3.0). Pregnant women were more likely anemic if they were in their 2nd trimester (AOR = 2.6; 95% CI: 1.9–3.6) or 3rd trimester (AOR = 1.6 95% CI: 1.1–2.3). Anemia remains highly prevalent among pregnant women in Cambodia. Public health interventions and policies to alleviate anemia should be prioritized and shaped to address these factors.


Introduction
Anemia is a major public health problem affecting roughly 37% (32 million) of pregnant women worldwide.Anemia during pregnancy is a leading cause of low birth weight, preterm birth, and perinatal/neonatal mortality.Women in developing countries are at higher risk of anemia due to micronutrient deficiencies, hemoglobinopathies, infections, or other socio-demographic factors, especially among pregnant women.This study describes the trends and identifies factors associated with anemia among pregnant women aged 15-49 years old in Cambodia.

Methods
We analyzed data from the Cambodia Demographic and Health Survey (CDHS) for 2005, 2010, and 2014.Data were pooled across the three survey years for all pregnant women aged 15-49 years.Survey weights were applied to account for the complex survey design of the CDHS.Descriptive statistics were estimated for key sociodemographic characteristics of the study population.We ran bivariate and multivariable logistic regressions to assess factors associated with anemia among pregnant women aged 15-49 years old.

Conclusion
Anemia remains highly prevalent among pregnant women in Cambodia.Pregnant women from poorer households, those who were further along in the pregnancy, and those living in coastal and sea regions were at greatest risk of anemia.Public health interventions and policies to alleviate anemia should be prioritized and shaped to address these factors.This statement is required for submission and will appear in the published article if the submission is accepted.Please make sure it is accurate.

Unfunded studies
Enter: The author(s) received no specific funding for this work.

ABSTRACT Introduction
Anemia is a major public health problem affecting roughly 37% (32 million) of pregnant women worldwide.Anemia during pregnancy is a leading cause of low birth weight, preterm birth, and perinatal/neonatal mortality.Women in developing countries are at higher risk of anemia due to micronutrient deficiencies, hemoglobinopathies, infections, or other socio-demographic factors, especially among pregnant women.This study describes the trends and identifies factors associated with anemia among pregnant women aged 15-49 years old in Cambodia.

Methods
We analyzed data from the Cambodia Demographic and Health Survey (CDHS) for 2005, 2010, and 2014.Data were pooled across the three survey years for all pregnant women aged 15-49 years.Survey weights were applied to account for the complex survey design of the CDHS.Descriptive statistics were estimated for key sociodemographic characteristics of the study population.We ran bivariate and multivariable logistic regressions to assess factors associated with anemia among pregnant women aged 15-49 years old.

Results
Anemia in pregnant women aged 15-49 in Cambodia decreased from 56% in 2005 to 53% in 2014.

Conclusion
Anemia remains highly prevalent among pregnant women in Cambodia.Pregnant women from poorer households, those who were further along in the pregnancy, and those living in coastal and sea regions were at greatest risk of anemia.Public health interventions and policies to alleviate anemia should be prioritized and shaped to address these factors.Keywords: Anemia, Cambodia, Pregnant Women, Maternal Anemia, CDHS INTRODUCTION Anemia during pregnancy occurs in both developed and developing countries and is associated with abnormal outcomes in pregnancy; e.g., greater risk for low birth weight, preterm birth, and perinatal/neonatal mortality [1].According to the World Health Organization (WHO), anemia is defined as hemoglobin (Hb) levels less than 11.0 g/dl in pregnant women [2].In 2019, it was estimated that anemia affected approximately 37% (32 million) of pregnant women worldwide , as many as half of all pregnant women in low-income and middle-income countries were diagnosed with anemia [3].
Furthermore, in Southeast Asia countries, 48% of pregnant women were anemia [4].Data from the Cambodian Demographic Health Survey (CDHS) 2014 suggest that the prevalence of anemia in Cambodia is higher among pregnant women compared with non-pregnant women (i.e., 53.2% compared to 45%) [5].
Anemia in pregnant women has severe consequences on health as well as social and economic development [6].contributing to low physical activity and increases maternal morbidity and mortality, especially among those with severe anemia [1] and those living in developing countries [7].The WHO estimates that 20% of maternal deaths are attributable to anemia [2].In Southeast Asia, half of all maternal deaths were due to anemia in 2016 [8].In Cambodia, anemia is affected 51.1% of pregnant women aged 15-49 years old in 2019 [9].Despite significant economic development in Cambodia over the past two decades, the prevalence of anemia in women has not substantially declined.
Pregnant women with anemia are twice as likely to die during or shortly after pregnancy compared to those without anemia [8].In many countries, anemia varies by socioeconomic factors such as education, household wealth status, occupation, and residence [10].Pregnant women aged 35 and older are more likely to develop anemia than younger aged pregnant women [11][12][13].Risk of anemia was greater among women living in the lowest wealth quintile, with limited education [14], and rural area [12,13].Similarly, repeated childbearing, inadequate water hygiene and sanitation status, and parasitic infection increases the risk of anemia in pregnant women [15].Factors associated with anemia during pregnancy in developing countries include nutritional deficiencies of iron, vitamin B12, folate, and parasitic diseases (e.g., malaria) [6,16,17].Compared to women who initiated antenatal care (ANC) in the first trimester, the odds of having anemia in pregnancy were significantly higher among pregnant women who initiated ANC in the second trimester (AOR=2.71)and third trimester (AOR=5.01)[18].
The proportion of anemia in Cambodia has slowly decreased in both pregnant and non-pregnant women.To further reduce the prevalence of anemia in Cambodia, improved understanding of its geographical distribution and associated risk factors are required.This enhanced understanding will help identify sub-populations at greater risk for anemia and prioritize geographic areas for targeted interventions.To our knowledge, there are no published peer-reviewed studies that assessed social and demographic factors associated with anemia among pregnant women in Cambodia over time.Hence, we explore temporal and geographic trends of anemia in pregnant women across the 2005, 2010, and 2014 CDHS surveys and identify factors associated with anemia among pregnant women.
Understanding these factors may further support policy development and programs with more effective strategies and interventions in Cambodia to reduce the prevalence of anemia among pregnant women and associated health risks such as maternal mortality.

Data
To analyze trends and factors associated with anemia in pregnant women in Cambodia, we used existing women's data from the 2005, 2010, and 2014 CDHS.The CDHS is a nationally representative population-based household survey that is regularly conducted roughly every 5 years.The survey typically uses two-stage stratified cluster sampling to collect the samples from all provinces that divided into sampling domains.In the first stage, clusters, or enumeration areas (EAs) that represent the entire country are randomly selected from the sampling frame using probability proportional to cluster size (PPS).The second stage then involves the systematic sampling of households listed in each cluster or EA.Interviews were then conducted with women aged 15-49 in selected households.Using the women's survey questionnaire, variables collected by the CDHS include births to women aged 15-49, sociodemographic characteristics, household assets that are used to calculate a household wealth index, health-related indicators and nutritional status, number of ANC visits and other pregnancy/delivery indicators for past births, and involvement in household decision making using questionnaires.It further includes height and weight measurements of women and children, hemoglobin level, malaria test, and vitamin A level [5].We restricted our sample to pregnant women with recorded hemoglobin level; which resulted in a total sample size of 1,629 pregnant women aged 15-49 (Fig 1).

Measurements Outcome variable
Anemia is the outcome variable used in the study.For women in CDHS, hemoglobin was measured by collecting capillary blood from a finger prick with the HemoCue 201+analyzer [19].The original variable for anemia level in the CHDS was recorded as a categorical variable with "not anemic", "mild anemia", "moderate anemia", and "severe anemia".Then, the original variable was recoded into the dichotomous variable Anemia, with mild, moderate, and severe anemia coded as Anemic = 1 and non-Anemic = 0. Wealth Index was coded as an ordinal level variable with richest =1 (reference category), richer = 2, middle = 3, poorer = 4, and poorest = 5 (we opted to use the wealth index that was provided by each respective survey year of the CDHS as opposed to calculating a wealth index across the pooled data.This decision was based on prior research that found wealth status designation was comparable across the CDHS provided indices and an index based on data pooled across years) [20,21].
Pregnancy Duration (Trimester) was coded as an ordinal level variable with 1 st = 1 (reference category), 2 nd = 2, and 3 rd = 3. BMI was coded as an ordinal level variable with Overweight or Obese = 1 (reference category), Normal = 2, and Underweight = 3. Prior Births was coded as an ordinal level variable with Less than 3 Births = 1 (reference category), 3-5 Births = 2, and 6 or more Births = 3 (3 observations had a missing value).Tobacco Use was coded as a dichotomous variable with No Tobacco Use = 0 and Tobacco Use = 1 (possible types of tobacco use included cigarettes, cigars, and chewing tobacco; 2 observations had a missing value).).Healthcare Barriers was coded as a dichotomous variable with No Barriers = 0 and 1 or more barriers = 1 (possible barriers reported included distance, money, and waiting time; 1 observation had a missing value).
Residence was a dichotomous variable representing urban vs. rural place of residence with Rural =1, Urban = 0. Phnom Penh was a dichotomous variable representing residence in the provincial area surrounding Phnom Penh vs. other regions of residence with Other Regions =1, Phnom Penh = 0. Cambodia's domains/provinces were regrouped for analytic purposes into a categorical variable with 4 geographical Regions that were coded as Plains = 1 (reference category), Tonle Sap = 2, Costal/sea = 3, and Mountains = 4. Health Facility Visit and Aborted Pregnancy were coded as dichotomous variables representing whether the respondent had visited a health facility in the past year or had ever terminated a pregnancy; results are not presented due to lack of statistical significance in bivariate analyses.

Analytic strategy
Data cleaning and analyses were performed using STATA version 16 (Stata Corp 2019, College Station, TX) [22].Additional visualization was performed using R version 4.2.0 ; the complex survey design of the CHDS was accounted for using the "survey" package [23,24].Sample weights and complex survey design were accounted for in both descriptive and logistic regression analyses.To convey temporal and geographic trends in anemia prevalence, weighted estimates of overall and region-specific temporal trends in anemia prevalence were visualized using the ggplot2 package in R [25], a series of maps illustrating provincial variation in the prevalence of anemia were also prepared using ArcGIS Desktop, Release 10.8.
Bivariate chi-square tests were used to assess significant associations between independent variables of interest including maternal demographic, household characteristics, geographical regions, and health-related) and anemia status.A significant level of any covariates at p-value < 0.15 were included in the multivariate logistic regression analysis [12].Some factors of interest, such as women's age, residence, geographic regions, survey years, and a total number of children ever born were included based on the literature and prior knowledge regardless of significance levels.
Bivariate logistic regression was used to analyze the magnitude effect of unadjusted associations between anemia and maternal bio-demographic and household characteristics, geographical regions, and health-related factors.Results are reported as Odds Ratios (OR) with 95% confidence intervals (CI).Multivariate logistics regression was then used to assess independent factors associated with anemia after adjusting for other potential confounding factors in the model.Results from the final multivariate model are reported as adjusted odds ratios (AOR) with 95% confidence intervals and corresponding p-values.Results from the final multivariable logistic regression model were considered as statistically significant based on a p-value less than 0.05 and 95% confidence intervals.
Multicollinearity were checked for some variables such as education and wealth index, Evaluations of effect medication were not statistically significant.Observations with missing values were omitted from the regression analyses.

RESULTS
A little over 60% of pregnant women included in the analysis were aged 21-30 years, and almost 98% were married (Table 1).Approximately 17% had no schooling, 52% had a primary education, 29% had a secondary education, and only 2.6% had a higher education.Roughly 45% were from poorest or poorer household wealth quintiles.Pregnancy duration was rather evenly distributed with 28% of pregnant women in their 1 st trimester, 37% in their 2 nd trimester, and 36% in their third trimester.
Slightly over 50% of pregnant women had a normal BMI, with another 33% were either overweight or obese.About 80% reported having fewer than 3 prior births.Only about 6% of pregnant women reported using tobacco.A majority (85%) of them resided in rural areas (Table 1).Regarding socio-demographic factors associated with anemia in pregnancy in logistic regression analysis, pregnant women were more likely to have anemia if they were aged 15-20 (OR = 1.5; 95% CI: 1.1-2.0)or aged 31-49 (OR = 1.6; 95% CI: 1.1-2.2) compared to pregnant women aged 21-30 (Figure 4).Pregnant women with no formal education were more likely to have anemia compared to women with a higher education (2.4; 95% CI: 1.1-5.1)as were women with only a primary level education (OR = 2.2; 95% CI: 1.1-4.5).Women working in agricultural or manual labor fields were more likely to have anemia compared to women working in professional fields (OR = 1.7; 95% CI: 1.2-2.3).Juxtapose pregnant women from the richest wealth quintile, pregnant women with lower wealth were more likely to have anemia; e.g., women from the poorest quintile were over 3 times as likely to have anemia (OR = 3.2; 95% CI: 2.1-4.7) and women from the poorer quintile were over 2 times as likely to have anemia (OR = 2.4; 95% CI: 1.6-3.6).
Health indicators associated with anemia in bivariate analysis included pregnancy duration, BMI, number of prior births, tobacco use, and barriers to healthcare.Pregnant women were more likely to have anemia if they were in their 2 nd trimester (OR = 2.5; 95% CI: 1.8-3.4)or their 3 rd trimester (OR = 1.5; 95% CI: 1.1-2.1)compared to pregnant women in their 1 st trimester.A normal BMI was also associated with anemia during pregnancy compared to a BMI indicating that a pregnant woman was overweight or obese (OR = 1.5; 95% CI: 1.1-1.9).Compared to having had fewer than 3 births, pregnant women with 6 or more prior births were more likely to have anemia (2.2; 95% CI: 1.2-4.2).Pregnant women using 1 type of tobacco were more likely to have anemia compared to pregnant women not using tobacco (1.9; 95% CI: 1.1-3.2);using 2 or more types of tobacco was likewise positively associated with having anemia (17.5; 95% CI: 3.7-83.3).Finally, reporting 1 or more barriers to accessing healthcare was associated with anemia during pregnancy (1.4; 95% CI: 1.1-1.8).Geographic regions of residence were likewise associated with a woman having anemia during pregnancy.Pregnant women from rural areas were more likely to have anemia compared to pregnant women from urban areas (1.7; 95% CI: 1.3-2.2).Likewise, pregnant women living outside of the area surrounding Phnom Penh were more likely to have anemia compared to pregnant women from the Phnom Penh area (1.6; 95% CI: 1.1-2.3).Coastal regions were positively associated with anemia compared to plains regions (1.9; 95% CI: 1.2-2.9)as were mountain regions (1.43; 95% CI: 1.04-1.98).
In the final multivariate logistic model (Figure 5), factors independently associated with anemia included age, wealth index, pregnancy duration, BMI, and geographical regions.Pregnant women were more likely to have anemia if they were aged 31-49 (AOR = 1.6; 95% CI: 1.0-2.3)compared to pregnant women aged 21-30.Compared to pregnant women from the richest wealth quintile, pregnant women from the poorest quintile were almost 3 times as likely to have anemia (AOR = 2.8; 95% CI: 1.76-4.9)as were women from the poorer quintile (AOR = 2.2; 95% CI: 1.3-3.9).Pregnant women were more likely anemic if they were in their 2 nd trimester (AOR = 2.6; 95% CI: 1.9-3.6)or 3 rd trimester (AOR = 1.6 95% CI: 1.2-2.3)compared to their 1 st trimester.Pregnant women with a normal BMI were more likely of developing anemia (AOR = 1.4; 95% CI: 1.0-1.8)compared to pregnant women who were overweight or obese.Pregnant women living in coastal regions had higher odds having anemia (AOR = 1.9; 95% CI: 1.2-3.0)compared to those living in plain region.Statistically significant associations were further visualized as predicted probabilities (see Figures 6-9 in the supplement).

DISCUSSION
Prevalence of anemia among pregnant women in Cambodia decreased slightly from 56% in 2005 to 53% in 2014.This prevalence level was relatively higher than many Southeast Asian countries during the same time period [26,27]; e.g., in Thailand the prevalence of anemia among pregnant women ranged from 31% in 2005 to 31.9% in 2016 and prevalence of anemia among pregnant women in Vietnam ranged from 33.8% in 2005 to 28.2% in 2015.The elevated prevalence of anemia among pregnant women in Cambodia may be explained by dietary habits, deficiencies in micronutrients such as iron or vitamin A, hemoglobinopathy, malaria infections, and helminths [16].Interventions to help mitigate anemia in Cambodia include the promotion of a diversified diet; recommendations that all pregnant women attend at least 4 ANC visit, receive a standard dose of 30-60 mg iron and 400 μg folic acid beginning as soon as possible during gestation, and iron-containing supplements no later than the first trimester of pregnancy; prevention and treatment of malaria; use of insecticide-treated bed nets; helminth prevention and control; delayed cord clamping; and increased birth spacing [28].However, some have noted that the factors addressed by these interventions cannot fully account for the elevated prevalence of anemia [29], hence the interest in better understanding associations between anemia and demographic, economic, and social factors as well as health-seeking behaviors across different parts of the country [30].
Our results suggest independent associations between anemia in pregnant women and age, wealth, pregnancy duration, BMI, and region of residence.Older aged pregnant women were more likely to have anemia compared to young pregnant women, which is consistent with previous studies [11][12][13] and may reflect biological and physical disadvantages with increased maternal age; e.g., developing gestational diabetes, high blood pressure during pregnancy, a mother having multiple pregnancies, and enduring the collective impact of exhausting labor-related complications [31][32][33].
Consistent with studies from Rwanda [34], Ethiopia [35], and Uganda [36], pregnant women were also more likely to have anemia if they were from the poorest wealth quintiles with the patterns of association between anemia and wealth exhibiting a dose response to increased poverty.Lower socioeconomic status is often associated with negative consequences regarding consumption of a healthy diet, greater chance of infection diseases, and less access to healthcare services [38].In contrast, individuals from higher socioeconomic groups have a comparative advantage that enables them to purchase sufficient food with greater variety and quality, thus protecting against anemia [39].In addition, pregnant women living in the coastal regions of residence were more likely have anemia compared to women living in plains regions.These differences in the prevalence of anemia might be due to variations in socioeconomic status, attention given to focused antenatal care and supplementation of iron sulfate throughout the pregnancy, dietary patterns, sample size, and geographical and lifestyle variations.Finally, pregnant women with a normal BMI were more likely of have anemia compared to pregnant women who were overweight or obese, which is surprising given prior studies suggesting that higher BMI is negatively associated with iron status among pregnant women [40].This association should be evaluated further in the future.
This study was conducted using pooled Demographic and Health surveys for 2005, 2010, and 2014, which enabled us to evaluate temporal and geographical trends in anemia among pregnant women using nationally representative data and generalize our findings to pregnant women throughout Cambodia.However, using cross-sectional data limits our ability to assess causal relationship among the associated factors that we identified.Using secondary data that was gathered to collect health and demographic data across a broad variety of variables related to child and maternal health enabled us to evaluate some of the factors likely associated with anemia among pregnant women, but other factors such as diet, nutritional supplements (Vitamin B12, folate); malaria infection, noncommunicable diseases such as hypertension and diabetes, and awareness about anemia were excluded from the analysis due to data limitations.Finally, the most recent round of CDHS data was gathered in 2014, which may no longer reflect present prevalence of anemia among pregnant women in Cambodia.
Future research should further evaluate these relationships and the general prevalence of anemia among pregnant Cambodian women once additional data becomes available (data gathering for the next round of Cambodia DHS data is underway, but delayed due to COVID-19).
Our findings suggest that the high prevalence of anemia among pregnant women in Cambodia declined only slightly over the 10-year period between 2005 and 2014.This is concerning given that anemia during pregnancy is a public health problem that should be actively addressed to mitigate the proximal and distal health risks associated with the condition.We identified age, socioeconomic status, higher BMI, and regions of residence as potential risk factors associated with anemia during pregnancy.
Public health practitioners and policy makers should consider demographic groups represented by these characteristics for better targeting interventions to address anemia among pregnant women in Cambodia.
disclosure statement that describes the sources of funding for the work included in this submission.Review the submission guidelines for detailed requirements.View published research articles from PLOS ONE for specific examples.
with the following details: Initials of the authors who received each award • Grant numbers awarded to each author • The full name of each funder • URL of each funder website • Did the sponsors or funders play any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript?• NO -Include this sentence at the end of your statement: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.• YES -Specify the role(s) played.• * typeset The author(s) received no specific funding for this work.Competing Interests Use the instructions below to enter a competing interest statement for this submission.On behalf of all authors, disclose any competing interests that could be perceived to bias this work-acknowledging all financial support and any other relevant financial or nonfinancial competing interests.

Fig 1 .
Fig 1. Selection process and the final sample size from the 2005, 2010, and 2014 CDHS.
Independent variablesIndependent variables included women's and household characteristics.Women's Age was categorized into an ordinal level variable with 15-20 years = 1, 21-31 years = 2 (reference category), and 32-49 years = 3. Women's Marital Status was coded into a dichotomous variable with Married = 1, Not Married = 0 (includes divorce, single, widowed, and separated).Women's Education was coded as an ordinal level variable with Higher = 1 (reference category), Secondary = 2, Primary = 3, No Education = 4. Women's Occupation was coded as a categorical variable with Professional = 1 (reference category; included clerical, technical, managerial, professional, sales, and services), Agriculture/Manual = 2 (included skilled and unskilled manual work), Not Working = 3 (1 observation had a missing value).
This study was approved by the National Ethical Committee for Health Research (Ref: 225 NECHR) Cambodia and the Institutional Review Board (IRB) of ICF in Rockville, Maryland, USA.The CDHS data are publicly accessible and were made available to us upon request to the DHS Program, ICF.Written consents were obtained from all participants before the interview with participants in the CDHS.
The overall prevalence of anemia among pregnant women decreased slightly from 56% in 2005 to 53% in 2014 (Fig 2).This decline varied across the four geographical regions with the highest prevalence of anemia in the coastal region in 2010 (66%).Plain region had the lowest prevalence of anemia across all survey years with prevalence levels in 2005 lower than the prevalence levels of other regions in 2014.Anemia was highest among pregnant women in Preah Vihear and Stung Treng provinces (74.3%), in Kratie province (73%), and in Prey Veng (65.4%) for 2005, 2010 and 2014 respectively (Fig 3).Pregnant women living in Phnom Penh had the lowest prevalence of anemia in 2005 and 2010 (i.e., 33.3% in 2005, 30.0% in 2010.In 2014, the lowest prevalence of anemia among pregnant women was observed in Takeo province (23.8%).

Fig 2 .Fig 3 .
Fig 2. Overall and Regional Trends of Anemia among Pregnant Women by Survey Year

Fig 5 .
Fig 5. Factors independently associated with anemia among pregnant women aged 15-49 years old in multivariate logistic regression analysis (n=1,567).

Figure
Figure The authors have declared that no competing interests exist.
Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation Powered by Editorial Manager® and ProduXion Manager® from Aries Systems CorporationMethods section of the manuscript.Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporationpresented in the study are available from (include the name of the third party and contact information or URL).This text is appropriate if the data are owned by a third party and authors do not have permission to share the data.
Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation

Table 1 .
Factors associated with anemia among study population in bivariate analysis (n=1,567)